Whole-brain white matter correlates of personality profiles predictive of subjective well-being

We investigated the white matter correlates of personality profiles predictive of subjective well-being. Using principal component analysis to first determine the possible personality profiles onto which core personality measures would load, we subsequently searched for whole-brain white matter correlations with these profiles. We found three personality profiles that correlated with the integrity of white matter tracts. The correlates of an “optimistic” personality profile suggest (a) an intricate network for self-referential processing that helps regulate negative affect and maintain a positive outlook on life, (b) a sustained capacity for visually tracking rewards in the environment and (c) a motor readiness to act upon the conviction that desired rewards are imminent. The correlates of a “short-term approach behavior” profile was indicative of minimal loss of integrity in white matter tracts supportive of lifting certain behavioral barriers, possibly allowing individuals to act more outgoing and carefree in approaching people and rewards. Lastly, a “long-term approach behavior” profile’s association with white matter tracts suggests lowered sensitivity to transient updates of stimulus-based associations of rewards and setbacks, thus facilitating the successful long-term pursuit of goals. Together, our findings yield convincing evidence that subjective well-being has its manifestations in the brain.

www.nature.com/scientificreports/ study aimed to investigate this by running a principal component analysis (PCA) that revealed the underlying commonalities between these psychological constructs.
One of the objectives of neuroscience is to map brain-behavioral connections which may yield important insights about the processes that possibly underlie psychological constructs. Several studies exist already on the gray and white matter correlates of personality measures [52][53][54][55][56] and of subjective well-being 57 . However, a limitation of these studies is that they have focused on one personality measure at a time (see 58 ). A likely possibility is that some personality measures cluster more often together than others, giving rise to personality "profiles" or "types" [59][60][61] . For example, high extraversion and high conscientiousness tend to cluster together but are both separate from high neuroticism 60,62 . Therefore, it might be wiser to investigate the neural correlates of personality profiles instead of individual factors. This has only very recently been attempted. For example, Li et al. 63 have looked into the grey matter correlates of personality profiles. However, no study to our knowledge has investigated the white matter correlates of personality profiles, particularly profiles that predict subjective well-being.
White matter tracts connect various grey matter regions and their integrity is a marker of how well the corresponding grey matter regions communicate with each other (e.g., 55 ). Therefore, individual variability in white matter tracts may underlie variability in personality profiles. Accordingly, in our study, we correlated the "positive personality profiles" from the PCA with the markers of white matter integrity. Because no other study has investigated the white matter correlates of personality profiles that are predictive of subjective well-being, we based our hypotheses on the few studies that independently probed relevant concepts (i.e., Big Five, BIS/BAS, emotion regulation strategies) in relation to white matter integrity.
For example, several studies have linked neuroticism to decreased integrity of white matter tracts in the cingulum (CNG 56,64 ), the uncinate fasciculus (UNC; 56,65 ), the body of the corpus callosum (CC 66,67 ) as well as increased integrity of the posterior CC, the corticospinal tract (CST), the inferior fronto-occipital fasciculus (IFOF; 68 ) and the inferior longitudinal fasciculus (ILF; 67,68 ). Extraversion correlates negatively with white matter integrity in the posterior CC 67,69 and the CNG and the IFOF 69 . Furthermore, the BIS scale correlates positively with the integrity of the CNG, UNC, IFOF and superior longitudinal fasciculus (SLF; 68 ). We note that some other studies have failed to find a meaningful relationship between white matter integrity and the Big Five dimensions 54,58,70 or the BIS/BAS 71 . By contrast, the association between the habitual use of cognitive reappraisal and white matter integrity has been rather consistent, implicating the UNC 72-75 and the CNG 72,73 . Given the above-reported correlates for isolated personality characteristics, we expected the implication of these areas in our profile study, too.
To measure white matter tracts, we used diffusion tensor imaging (DTI) tract-based spatial statistics, which is a commonly used voxel-based statistical framework for understanding white matter integrity 76 . To operationalize white matter integrity, we looked at widely used measures in DTI: (a) fractional anisotropy (FA), a measure that describes the directionality strength of local white matter tracts, (b) axial diffusivity (AD), a measure of the degree of diffusion of water molecules parallel to the axonal tracts, and (c) radial diffusivity (RD), a mean diffusion coefficient of water molecules diffusing orthogonally to the axonal tracts. These diffusivity measures provide complementary information about white matter integrity: as FA and AD values increase (integrity increases), RD values decrease.

Results
Principal component analysis results. The PCA analysis revealed that the 16 behavioral measures loaded on five principal components (eigenvalue > 1, serving as a cutoff) (Table 1). Together, these five principal components or personality profiles explained 60.8% of the total variance (Fig. 1).
The first component, which we call "Optimism" loaded the LOT Optimism, COS Optimism and Satisfaction with Life positively and LOT Pessimism negatively. The second component, dubbed "Avoidant behavior", loaded the BIS, BFI Conscientiousness and BFI Neuroticism positively and BAS Fun Seeking negatively. The third component, "Short-term approach behavior" loaded BFI Extraversion, BFI Agreeableness and BAS Fun Seeking positively but ERQ Suppression negatively. The fourth component, "Long-term approach behavior", loaded all three BAS components and BFI Openness positively. Finally, the fifth component "Pessimistic reappraisal" loaded COS Pessimism and ERQ Reappraisal positively (Table 1).
White matter voxel-based results. The tract-based spatial statistics correlations between personality profiles and diffusion maps are presented with Table 2. Of these five PCA components, "Optimism" (PCA 1), "Short-term approach behavior" (PCA 3) and "Long-term approach behavior" (PCA 4) revealed tract-based findings for the probabilistic diffusion maps. Specifically, the "Optimism" component correlated positively with AD values in the right hemisphere exclusively (Fig. 2): the corticospinal tract (CST), the superior longitudinal fasciculus (SLF), anterior cingulum bundle (CNG), anterior corpus callosum (CC), anterior thalamic radiation (ATR) and uncinate fasciculus (UNC). The component for "Short-term approach behavior" correlated negatively with the FA values in the left hemisphere exclusively, namely the splenium of the CC, inferior longitudinal fasciculus (ILF), and UNC (Fig. 3). This component further correlated positively with the RD values in the right UNC/inferior fronto-occipital fasciculus (IFOF) and right SLF and left CNG (Fig. 4). Lastly, the component for "Long-term approach behavior" correlated positively with the RD values in the right UNC (Fig. 5).

Discussion
Our study is the first to investigate the white matter correlates of personality profiles that are predictive of subjective well-being. We used PCA to determine the possible profiles onto which dispositional optimism, Big Five dimensions, BIS/BAS, ERQ and SWL would load. We then searched for whole-brain white matter correlations with these profiles, and we based our hypotheses on past structural findings for each separate psychological construct. The PCA revealed five distinct profiles, three of which correlated to white matter measures: (a) "Optimism" We found that the "Optimism" profile correlated positively with AD values in white matter tracts exclusively in the right hemisphere: the CST, the SLF, and the anterior CNG, CC and ATR. Similar to FA values, the AD reflects the magnitude of diffusion parallel to fiber tracts and thus the integrity of axons 77,78 . The exclusivity of our findings in the right hemisphere is in line with the proposed functional asymmetry between the left and right hemispheres concerning complementary modes of processing incoming information (e.g. 79,80 ). While the left hemisphere processes the information in a strictly sequential and unambiguously understood monosemantic context 81 , the function of the right hemisphere is to simultaneously capture a vast number of possible connections and to integrate them in an ambiguous but polysemantic context [81][82][83] . Because of this functionality, the right  [88][89][90] . The implicit self is a highly integrative construct that processes vast amounts of self-relevant information from cognitive (e.g., autobiographical memories), motivational (e.g., values, needs) and affective (e.g., emotions) systems in parallel 87,91 . Because personal experiences are inherently perceived as positive in healthy individuals 92 , a functional implicit self is crucial in maintaining a positivity bias by assimilating negative affective experiences within a network of predominantly positive experiences 81,93 . Due to this holistic nature, the implicit self is believed to be a function of the right hemisphere 87,90 . The incapacity to regulate negative affect and display a (somewhat normal) positivity bias underlies emotional disorders such as depression, alexithymia and suicidal ideation, which are characterized both by a lack of optimism bias 53 and a functionally deficient right hemisphere 79,81,94 , including decreased integrity of white matter tracts 95 . Our study thus supports previous findings that the right hemisphere is necessary for healthy individuals to express their positivity bias.
Regarding the individual tracts in the right hemisphere underlying "Optimism", the CST was the strongest finding in terms of cluster size. The integrity of the CST is associated with a lower baseline excitability threshold, i.e. the minimum intensity at which the motor system can evoke a motor response 96,97 . At the same time, CST excitability indexes the degree of "wanting" a reward 98 ; see also 99 and the certainty of upcoming rewards 100,101 . Our finding that dispositional optimism is foremost associated with the integrity of the CST makes it thus tempting to speculate that optimism is more embodied than we may believe. Could optimism predispose us not Table 2. TBSS randomized results with TFCE at p < .05 after 5000 permutations. The correlation results for behavior data with DTI maps for axial diffusivity (AD), radial diffusivity (RD) and fractional anisotropy (FA) are presented along with the cluster size, peak voxel coordinate and tract anatomy of the findings. LOT-Life LOT-Life Orientation Test. SWLS-Satisfaction With Life Scale. COS-Comparative Optimism Scale. BIS-Behavioral Inhibition System. BAS-Behavioral Approach System. BFI-Big Five Inventory. A plus (minus) sign depicts positive (negative) contributions of the behavioral measures to the principal components. www.nature.com/scientificreports/ only toward expecting good things to happen but also toward motor readiness to go after these rewards? After all, one of the aspects of dispositional optimism bringing an adaptive advantage in life 102 is its ability to make us effortlessly engage in our goals 103 .
Other individual white matter tracts associated with the "Optimism" profile were the dorsal SLF, and the anterior CNG, CC and ATR. The dorsal SLF is essential to the dorsal attention pathway [104][105][106] and its integrity relates to measures of sustained goal-directed visuospatial attention in children 107,108 and adults [109][110][111] . That optimism and attention deployment are critically linked is demonstrated in various behavioral and neuroimaging studies ( 112-115 , for a theoretical account, see 116 ). Interestingly, the integrity of the right SLF has further been connected to global visual motion sensitivity 117 , i.e. the ability to perceive and infer the overall movement trend of a multitude of stimuli (e.g. moving dots) with otherwise random motion. In other words, the right SLF supports seeing the forest and not the trees. This holistic perception ability is likely due to the right-side hemispheric lateralization, as discussed above. The overwhelming evidence suggests that the right SLF is involved in the endogenously controlled capacity to actively detect, follow, and respond to relevant (holistic) stimuli over prolonged periods of time. Although the SLF might not be specific to optimism bias, it might maintain it when other mechanisms are in place to generate it, e.g. by supporting long-term pursuit of desirable outcomes 118 . www.nature.com/scientificreports/ The remaining white matter tracts whose integrity correlated with the "Optimism" component, i.e. the anterior CNG, CC, and ATR, connect brain regions that are part of the anterior midline core of the default mode network (DMN). Notably, the functional connectivity between the core nodes of the DMN positively correlates with the integrity of the CC 119-121 , CNG 122-124 and the ATR 122,125 . The anterior midline node of the DMN supports internally directed thought and self-referential processing 126,127 , including simulating one's (mostly optimistically biased) future [128][129][130] . The integrity of the CC, in particular, has been associated with a higher dispositional optimism 131,132 and a higher resistance to updating personal beliefs in a pessimistic direction 133,134 . Furthermore, the gray matter endings of the anterior CC, CNG and ATR all overlap in the ventromedial prefrontal cortex (vmPFC; [135][136][137][138][139] ). There is highly converging evidence pointing to the involvement of the vmPFC in optimism bias 53,[140][141][142][143][144] , and activity in the vmPFC also correlates positively with subjective well-being 145 . Thus, the correlation between the optimism profile and the white matter tracts of vmPFC is not surprising.
In sum, the "Optimistic" personality profile correlated with white matter tracts that suggest a motor readiness to act upon the conviction that desired rewards are imminent (CST), a sustained capacity for visually tracking rewards in the environment (SLF) and an intricate network for self-referential processing that helps regulate negative affect and maintain a positive outlook on life (anterior CNG, CC, ATR).
We called the third PCA factor "Short-term approach behavior" because impulsivity (indexed by BAS Fun Seeking; 146 ), extraversion and agreeableness positively loaded on it. Impulsivity, i.e. the motivation to spontaneously go after novel rewards, is a core part of both extraversion 147,148 and agreeableness 149 , so their clustering is not surprising. Furthermore, ERQ Suppression loaded negatively, suggesting an inability to suppress impulsive urges. We note that impulsivity is operationally split into motor impulsivity and cognitive impulsivity [150][151][152][153] . Motor impulsivity is similar to motor readiness and correlates with CST integrity and excitability (e.g. 154 , see also "Optimism" profile above). By contrast, cognitive impulsivity refers to the inability to compare immediate consequences and the future events with each other and, consequently, the inability to see reasons for delaying immediate satisfaction. The relevant measures on our third PCA factor, namely BAS Fun Seeking 146 ,   55 . Interestingly, individuals with either behavioral or substance addiction show more extensive impairments of the integrity of the CC splenium [155][156][157] and ILF 158,159 . These extensive impairments of both CC and ILF are, in turn, inversely related to the levels of self-reported impulsivity 156 . We thus propose that a minimal loss of integrity in these tracts lifts certain barriers and predisposes individuals to be more outgoing and carefree in approaching people and rewards 160,161 , but too extensive a damage to their integrity is a risk factor for addiction and clinical impulsivity.  www.nature.com/scientificreports/ We termed the fourth PCA factor "Long-term approach behavior" due to the high loading of BAS Drive (highintensity pursuit of desired goals) and BAS Reward Responsiveness (positive affective experience in response to rewards) and, to a lower extent, the contributions of BAS Fun Seeking and Openness. Both BAS Drive and BAS Reward Responsiveness are associated with vigorous pursuit of long-term rewards despite physical or mental challenges 162 , while BAS Fun Seeking points to the spontaneous pursuit of novel rewards 146 . Although, taken in isolation, the three BAS components point to different time windows of pursuing rewards, the combined three components are compatible with pursuing long-term goals. A high BAS Drive safeguards the behavioral maintenance of long-term goals despite obstacles while a high BAS Fun Seeking component (combined with the high BFI Openness) ensures the flexibility and readiness to spontaneously seize unexpected alternative ways of attaining the long-term goal. Finally, a high BAS Reward Responsiveness ensures appropriate positive emotional reactions when attaining each milestone on the way to achieving the final behavioral goal, a process that ensures goal pursuit.
In terms of brain structures, the "Long-term approach behavior" component correlated positively with RD values in the right UNC/IFOF: the lower the integrity between the anterior temporal lobes and the frontal cortex, particularly the orbitofrontal cortex 163,164 , the more prominent the long-term approach behavior. It was proposed that the UNC allows temporal lobe-based stimulus associations (e.g. between the physical properties of a stimulus and the emotions associated with it) to modify behavior via interactions with the orbitofrontal cortex 163,164 . These interactions between the temporal lobe and the orbitofrontal cortex would be instrumental in ensuring that stored stimulus associations reflect up-to-date reward and punishment history. Applied to the present data, one may therefore speculate that the successful behavior of keeping eyes on an end goal depends on not always allowing up to date (and likely transitory) reward and punishment information to interfere with the end goal established much earlier on.

Limitations, strengths and conclusions.
We would like to point out that the analyzed sample consisted mostly of females. Given that gender plays a role in brain structure and morphology 165 , future studies should include a balanced sample of males and females. We tried to mitigate these confounding influences by taking age, gender, and total intracranial volume as the covariates of no-interest. Our study has the strength of focusing on personality profiles as opposed to isolated constructs and investigating the white matter correlates of the profiles predictive of subjective well-being. The correlates of an "Optimistim" personality profile suggest (a) an intricate network for self-referential processing that helps regulate negative affect and maintain a positive outlook on life, (b) a sustained capacity for visually tracking rewards in the environment and (c) a motor readiness to act upon the conviction that desired rewards are imminent. Correlates of a "Short-term approach behavior" profile were indicative of minimal loss of integrity in white matter tracts supportive of lifting certain behavioral barriers, possibly allowing individuals to act more outgoing and carefree in approaching people and rewards. Lastly, a "Long-term approach behavior" profile's association with white matter tracts suggests lowered sensitivity to transient updates of stimulus-based associations of rewards and setbacks, thus facilitating the successful long-term pursuit of goals.
Given that personality plays a crucial role in subjective well-being, identifying the morphological correlates of personality profiles may provide important information for potential therapeutic interventions. For example, an optimistic personality profile was the strongest predictor of subjective well-being both psychologically in terms of the PCA variance and in terms of structural correlates. Some of the putative mechanisms underlying such a profile are domain-general and not specific to optimism per se, e.g., an intact system for sustained attention to holistic stimuli supported by the right SLF. It will be interesting to investigate whether trainings on targeted activities that tap into the functions of the right SLF might transfer to subjective well-being by increasing optimism. Previously, we showed that an attention bias modification training could successfully enhance optimism bias 118 . Future studies can investigate whether such trainings can also boost subjective well-being.

Methods
Participants. We recruited 99 healthy candidates with an age criterion between 18 and 40 years (mean age = 24.03 ± 4.39, 62 females). Recruitment was made through emails, flyers and the local participant pool at the University of Bern, Switzerland. Exclusion criteria included self-reported neurological conditions, psychoactive substance usage, left-handedness, and magnetic resonance imaging (MRI) specific problems such as failed image reconstruction and excessive motion artefacts observed on structural scans. For their participation, the students received either course credits or 25 Swiss francs (CHF). Participants gave written informed consent, in accordance with the guidelines of the Declaration of Helsinki. Experimental procedures were approved by the ethics committee of the canton Bern, Switzerland. Five participants were excluded due to incomplete questionnaires. Both DTI and T1-weighted structural scans from all participants qualified visual inspection. Final analysis was conducted on 94 participants. Psychological assessment. Using 76 , the voxel-based approach used in this paper, utilizes extracted and skeletonized white matter tracts in the FA images of all participants. TBSS has been introduced to overcome the problems associated with the use of standard registration algorithms in other voxel-based approaches 177 . We used the FSL software (http:// fsl. fmrib. ox. ac. uk/ fsl/ fslwi ki) for the preprocessing prior to TBSS. First, eddy correction (eddy_correct) was applied on DTI images to address eddy current-induced distortions and motion artefacts. After this step, the DTI images were processed with the FMRIB Software Library's diffusion toolbox (DTIFIT; 178,179 ), which fits a diffusion tensor model at each voxel and generates three eigenvalues (λ 1 , ), axial diffusivity (AD = λ 1 ) and radial diffusivity (RD = 1+ 2 2 ) maps were hence generated. Details of the underlying processes in the TBSS analysis stream are extensively covered in the literature [180][181][182][183] . In brief, for the FA maps, firstly a preprocessing erosion step was applied to remove brain edge artefacts and nullify intensities of end slices, to reduce false positives from tensor fitting. Later, FA maps across the participants were non-linearly registered to a standard template in MNI space (FMRIB58_FA template). Following registration, all FA maps were transformed to the standard MNI space with an isotropic voxel size of 1mm 3 , by applying the registration warps to individual images. The standardized maps were merged into a single 4D image, mean FA and its subsequent skeletonized version (WM skeleton) were created. The skeleton was restricted to WM with a threshold of FA = 0.2 and standardized FA maps were projected onto the skeleton. Non-FA maps (RD and AD) were also transformed to their respective skeletonized forms by applying the FA-derived registration and projection vectors. Finally, skeletons across the DTI maps were smoothed with an 8 mm FWHM Gaussian kernel. To find the positive and negative associations between the principal components (from PCA) and the DTI maps (FA, AD, and RD), we performed a non-parametric permutation analysis (t-test) using randomize (in FSL) with 5000 permutations, with age, gender, and total intracranial volume (TIV) as the covariates of no-interest. Only the clusters surviving a family-wise error (FWE) multiple comparison at p < 0.05 are reported.
Ethics approval. All procedures performed in studies involving human participants were approved by the ethical committee of the University of Bern according to the standards of the Declaration of Helsinki. Consent to participate. All participants provided written consent.

Data availability
Under the Swiss guidelines of data protection (Ordinance HFV Art. 5), the MRI images generated and analyzed during the current study can be made available from the corresponding author on a case-by-case basis.